FIELD NOTE 03 / AI STRATEGY

Not every task deserves AI.

The right question is not “Where can we add AI?” It is “Where is valuable work repeatedly losing time, context, or momentum?”

AI projects often begin with the technology and search for a use case afterward. That creates impressive demonstrations that never become dependable parts of the business.

A useful automation begins with friction. The work is repetitive enough to justify a system, consequential enough to matter, and structured enough to evaluate.

Look for repeated decisions

AI is often most useful when people repeatedly read similar information, classify it, summarize it, draft a response, or choose among a known set of next actions. Lead intake, call summaries, document review, routing, and service recommendations are common examples.

Measure the cost of lost context

Some processes are slow because information moves between tools or people without its original context. An automation that preserves why a request exists can be more valuable than one that merely completes a task faster.

Keep consequences proportional to oversight

The higher the risk of a wrong answer, the more human review the system needs. Drafting a follow-up message and automatically approving a financial decision should not have the same level of autonomy.

Automate the repeatable work. Keep people responsible for judgment, relationships, and consequential decisions.

Define success before the build

A serious project should have an observable outcome: faster response, fewer missed inquiries, cleaner data, shorter preparation time, more completed bookings, or fewer manual handoffs. If success cannot be described, the system is not ready to build.

Prefer the smallest useful version

Start with one workflow, one audience, and a controlled set of actions. A narrow system that works reliably earns the right to expand. A broad system that performs unpredictably creates more supervision than it removes.

Design an exit

The business should know what happens when the model is uncertain, an integration fails, or a person needs to take over. Good automation includes escalation, logging, and a path back to manual operation.

The goal is not to make a business appear more automated. It is to make the experience faster, clearer, and more human wherever technology can genuinely help.